2 citations · 5 across the 32 of their papers we have counts for
6 papers · 1 filter
Code Is More Than Text: Uncertainty Estimation for Code Generation
Yuling Shi, Caiqi Zhang, Yuexian Li +4
Large language models (LLMs) are increasingly deployed as code generators, where silently wrong programs pose real safety and reliability risks. Reliable uncertainty estimation (UE…
HEART-Bench: Do LLM Agents Exhibit Human-like Psychology?
Weihan Peng, Chenxu Zhang, Qianao Wang +7
While LLM agents have demonstrated remarkable task-oriented abilities such as planning, reasoning, and action, few works have treated them as complete human personalities where emo…
Reasoning in Trees: Improving Retrieval-Augmented Generation for Multi-Hop Question Answering
Yuling Shi, Maolin Sun, Zijun Liu +4
Retrieval-Augmented Generation (RAG) has demonstrated significant effectiveness in enhancing large language models (LLMs) for complex multi-hop question answering (QA). For multi-h…
Robust Preference Alignment via Directional Neighborhood Consensus
Ruochen Mao, Yuling Shi, Xiaodong Gu +1
Aligning large language models with human preferences is critical for creating reliable and controllable AI systems. A human preference can be visualized as a high-dimensional vect…
LongCodeZip: Compress Long Context for Code Language Models
Yuling Shi, Yichun Qian, Hongyu Zhang +2
Code generation under long contexts is becoming increasingly critical as Large Language Models (LLMs) are required to reason over extensive information in the codebase. While recen…
SWE-QA: Can Language Models Answer Repository-level Code Questions?
Weihan Peng, Yuling Shi, Yuhang Wang +3
Understanding and reasoning about entire software repositories is an essential capability for intelligent software engineering tools. While existing benchmarks such as CoSQA and Co…